GeminiDB Time Series IoV Solution

Scenarios

Fueled by immense popularity of intelligent new energy vehicles, time series data generated in real time experienced tremendous growth. There were urgent demands for vehicle enterprises and owners to query the real-time status of vehicles, but the traditional HBase-based vehicle monitoring platform cannot meet the requirements.

Solution Overview

The GeminiDB time series IoV solution is designed for real-time queries of vehicle data through the dedicated Influx API, which parses, sorts, merges, analyzes, and writes millions of time series data of vehicles in real time. This solution supports high compression ratio and separation of cold and hot data, effectively reducing costs.

Advantages

• Parsing and writing massive volumes of data in real time; simplifying application development

HBase: Thousands of monitoring metrics reported by vehicles are written into HBase as character strings. When an application reads a metric, it needs to read and parse all character strings. This process is complex and inefficient.

GeminiDB Influx API: Thousands of monitoring metrics reported by vehicles are directly written into GeminiDB Influx instances as thousands of columns. Metrics can be directly queried and without being parsed again.

• Automatically sorting and combining data; simplifying the intermediate process

Multi-dimensional metric data reported at the same time point by vehicles is processed by different components under different network delays, so the data cannot be reported and written at a time in sequence.

HBase: Applications need to use Spark to combine and sort HBase data, which is complex and cannot meet real-time query requirements.

GeminiDB Influx API: When time series data is written, it is automatically merged and sorted. Applications can directly access GeminiDB Influx instances to obtain the result.

• Real-time analysis

HBase: Generally, historical data is dumped to Hudi. Applications have to find a vehicle VIN on Elasticsearch based on metrics and then query the metric data in Hudi based on the VIN for analysis. Interaction among multiple systems is complex, which cannot support real-time analysis of massive volumes of data.

GeminiDB Influx API: Data can be queried and analyzed based on metrics at a time. Just one database is enough for effective real-time query and analysis.

• High compression ratio

HBase: The compression algorithm can be set only by column family. Only the GZIP, Snappy, LZO, and LZ4 algorithms are supported.

GeminiDB Influx API: Different compression algorithms are used for data types of each column. Multiple compression algorithms, such as Simple8b, Delta, Delta-Of-Delta, RLE, ZigZag, ZSTD, Snappy, and bit-packing, are supported. The compression ratio is 10 times that of HBase.

• Separation of hot and cold data

Users can configure hot and cold data policies to automatically dump data to cold storage without changing applications, which effectively reducing the overall cost.